SPSS Decision Trees

IBM® SPSS® Decision Trees helps you better identify groups, discover relationships between them and predict future events. This module features highly visual classification and decision trees that enable you to present categorical results in an intuitive manner, so you can more clearly explain categorical analysis to non-technical audiences. It includes four tree-growing algorithms, giving you the ability to try different types and find the one that best fits your data.

The module provides specialized tree-building techniques for classification within the IBM SPSS Statistics environment. The four tree-growing algorithms include:

CHAID—a fast, statistical, multi-way tree algorithm that explores data quickly and efficiently, and builds segments and profiles with respect to the desired outcome.

Exhaustive CHAID—a modification of CHAID, which examines all possible splits for each predictor.

Risk and classification tables

Tree-based classification model

The Decision Tree procedure creates a tree-based classification model. It classifies cases into groups or predicts values of a dependent (target) variable based on values of independent (predictor) variables.